datasets: []
license: cc-by-nc-4.0
language:
- en
tags:
- automation
- home
- assistant
pipeline_tag: text-generation
Home 1B v2
The "Home" model is a fine tuning of the Phi-1.5 model from Microsoft. The model is able to control devices in the user's house via a Home Assistant integragion. The fine tuning dataset a custom curated dataset designed to teach the model function calling.
The model is quantized using Lama.cpp in order to enable running the model in super low resource environments that are common with Home Assistant installations such as Rapsberry Pis.
The model can be used as an "instruct" type model using the ChatML prompt format. The system prompt is used to provide information about the state of the Home Assistant installation including available devices and callable services.
Example "system" prompt:
You are 'Al', a helpful AI Assistant that controls the devices in a house. Complete the following task as instructed with the information provided only.
Services: light.turn_off(), light.turn_on(rgb_color,brightness), fan.turn_on(), fan.turn_off()
Devices:
light.office 'Office Light' = on;80%
fan.office 'Office fan' = off
light.kitchen 'Kitchen Light' = on;80%;red
light.bedroom 'Bedroom Light' = off
Output from the model will consist of a response that should be relayed back to the user, along with an optional code block that will invoke different Home Assistant "services". The output format from the model for function calling is as follows:
turning on the kitchen lights for you now
```homeassistant
{ "service": "light.turn_on", "target_device": "light.kitchen" }
```
Training
The model was trained as a full fine-tuning on an RTX 3090 (24GB). It was trained for ~2x as many tokens as the v1 version of the model.
Evaluation
This model acheives a 88.52% score for JSON function calling accuracy on the test dataset. The v1 model acheives a 76.78% score on the same test.
Datasets
Snythetic Dataset for SFT - https://github.com/acon96/home-llm
License
This model is a fine-tuning of the Microsoft Phi model series (MIT License) and utilizes datasets thare are licensed under CC BY-NC-4.0. As such this model is released under the same non-commerical Creative Commons License. The fine-tuned model is shared FOR RESEARCH PURPOSES ONLY. It is not to be used in any sort of commercial capacity.